Does Q&A Boost Engagement? Health Messaging Experiments in the United States and Ghana
通过美国和加纳的实地实验，研究问答式信息传递相比直接陈述能否提升公众对健康信息的获取和行为改变，发现问答格式能显著增加特定主题的信息搜索，但对一般信息效果有限。
Effective information sharing is critical for the success of organizations and governments. Because information that is easy to access is more likely to be adopted, leaders often minimize friction in information delivery. However, one type of friction may increase engagement: piquing curiosity by posing relevant questions prior to sharing information. To test this, we shared identical information about COVID-19 in either question-and-answer format or via direct statements across two preregistered field experiments in Ghana and Michigan (total n = 49,395). Q&A-style communication increased information seeking about directly related topics (e.g., how to wear a mask properly) by 1.0 percentage point (216%) in Ghana and by 1.1 percentage points (19%) in Michigan (p’s < 0.001) and increased self-reported behavior change by 1.3 percentage points (4%) in Michigan (p = 0.002). However, sharing information in Q&A format did not increase interest in general COVID-19 information in either setting, suggesting that the impact of Q&A-style messaging on information seeking may be issue specific. In Michigan, both Q&A-style and direct statement messaging produced less information seeking than sending no informational messages, likely because of differential attrition: the more texts participants received, the more likely they were to opt out of receiving messages, which made it impossible for them to seek more information via text. In a follow-up implementation experiment with social media ads (a messaging strategy without attrition challenges), Q&A-style ads generated 9%–11% more unique clicks to the CDC website per dollar spent than ads that directly stated information about vaccines (p < 0.001). We speculate that Q&A-style information delivery may stimulate curiosity, driving its benefits. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: The authors thank the National Science Foundation [RAPID Grant 2033321], the Bill and Melinda Gates Foundation, Northwestern University’s Global Poverty Research Lab, Stanford University’s Golub Capital Social Impact Lab, Harvard Business School, the University of Pennsylvania, the AKO Foundation, John Alexander, Mark J. Leder, and Warren G. Lichtenstein for funding support. This work was also supported by Grand Challenges in Global Health. Supplemental Material: The supplementary materials and data files are available at https://doi.org/10.1287/mnsc.2024.04405 .